CN107024711A - A kind of approximating method of scintillation pulse digitized signal - Google Patents
A kind of approximating method of scintillation pulse digitized signal Download PDFInfo
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- G01T1/00—Measuring X-radiation, gamma radiation, corpuscular radiation, or cosmic radiation
- G01T1/16—Measuring radiation intensity
- G01T1/20—Measuring radiation intensity with scintillation detectors
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Abstract
The present invention provides a kind of approximating method of scintillation pulse digitized signal, comprises the following steps：The prior model of selected scintillation pulse is biexponential model；The sampled point of classical pulsed in selected scintillation pulse database, including eight voltage threshold sequences and eight time point sequences；The temporal translation of curve progress to biexponential model obtains time array；Four initial default parameters of object function are set to 1, initial parameter array is saved as；Time array, scintillating target function etc. are input in the literary Burger Ma Kuaerte fitting functions of row, is fitted and obtains fitting parameter；For each scintillation pulse in scintillation pulse database, it is repeated in, completes the fitting of all scintillation pulses；The energy value of k-th of pulse is obtained to the object function integration after fitting；Solve equation the time for extracting pulse and energy information.The energy resolution that the present invention is obtained is obviously improved, and can ensure the degree of accuracy and the stability of information extraction while treatment effeciency is improved.
Description
Technical field
The present invention relates to the field of signal processing of medicine equipment, relate more specifically to a kind of flicker arteries and veins in digital PET fields
Rush the approximating method of digitized signal.
Background technology
Positron emission tomography (Positron Emission Tomography, full text abbreviation PET) is by catching
Catch the γ photons sent by positron annihilation in human body and obtain tracer dividing in human body using positron radionuclide for mark
Cloth situation, so obtain organ function, metabolism etc. pathophysiological features.Energy, position entrained by acquisition γ photons is with timely
Between the accuracy of information directly influence the performance of system imaging.Scintillation detector is used for high energy particle (particle such as γ, X)
Capture and the measurement of corresponding energy sedimentary information, because it has, detection efficient is high, time response is fast and information measurement is accurate
The features such as, it is widely used in radiation detection and imaging field.Scintillation detector is generally by scintillator (such as BGO, LYSO, LaBr
Deng) and optical-electrical converter (such as PMT, SiPM, APD) constitute, the particle such as incident γ, X and scintillator interaction generation
Fluorescence is then converted to corresponding scintillation pulse by fluorescence, electrooptical device.Scintillation pulse is digitized, at data signal
The digital scintillation pulse of technical Analysis is managed to extract the energy sedimentary information of particle, by further analyze digital scintillation pulse,
Optimization and upgrading processing algorithm can improve constantly the precision of particle energy sedimentary information extraction, improve the property of scintillation detector
Can, and then improve the image quality of PET system.
A kind of method of digital scintillation pulse sampling is multi thresholds sampling (Multi-Voltage Threshold, below letter
Claim MVT) method, this method reasonably sets multiple voltage thresholds according to the feature of scintillation pulse, by being crossed to scintillation pulse
The final digitized sampling for realizing scintillation pulse of digitlization of the time of voltage threshold.When being coordinated using a small amount of threshold comparator
Between digital quantizer (Time-to-Digital Converter, abbreviation TDC) just can design corresponding MVT sample circuits and enter
The MVT samplings of line flicker pulse, complete the acquisition of corresponding digital scintillation pulse.MVT methods are used for the digitlization of scintillation pulse
With the extraction of particle energy sedimentary information, have the advantages that excellent performance, Project Realization be simple, low in hardware cost.It is existing to grind
Study carefully result to show, the digital scintillation pulse obtained using the MVT sample circuits of 3~8 threshold values coordinates the flicker arteries and veins based on priori
The accurate acquisition of particle energy sedimentary information can be achieved in the digit pulse analysis method for rushing shape information.
One of existing digit pulse analysis method is least-squares algorithm, and it includes Newton method, gradient method etc..However,
Existing most of least-squares algorithm takes pole when the digital scintillation pulse signal got to PET system is fitted
It is long, the scintillation pulse number of the big order of magnitude is added, causes inefficiency in actual process, from gathered data to obtaining medical science
Image it is time-consuming long, can not gradually meet industrial requirement, and there is these algorithms certain use to limit, it is impossible to
Gratifying balance is reached in stability, accuracy.It is the thought with least square to have some fitting algorithms in addition, is passed through
Select two parameters in biexponential model to be fitted, realize that the regular hour imitates to sacrifice the cost of pulse integrality
Rate, still, acquired scintillation pulse time, energy information be not exactly accurate, finally PET system temporal resolution and
Certain deterioration is had in energy resolution.
Literary Burger-Ma Kuaerte (Levenberg-Marquardt) method of row is one kind in optimization algorithm, is also to use
Widest non-linear least square iterative algorithm, it is to seek maximum (small) value using gradient, is declined between Newton method and gradient
A kind of nonlinear optimization method between method, while there is gradient method and Newton method, therefore, its application field
Widely, such as：Economics, management optimization, network analysis, mechanically or electrically optimal design, design etc..Therefore, in order to enter
One step improves the picture quality after pulse is rebuild, if it is possible to be applied to row text Burger-Ma Kuaerte algorithms to obtain through MVT samplings
Scintillation pulse digitized signal processing, will be the best fit side that takes into account the composite factors such as efficiency, the degree of accuracy, stability
Method, can better meet industrial requirement.
The content of the invention
It is an object of the invention to provide a kind of approximating method of scintillation pulse digitized signal, so as to solve prior art
The problem of digit pulse approximating method can not take into account efficiency, the degree of accuracy and stability.
In order to solve the above-mentioned technical problem, the technical scheme is that providing a kind of plan of scintillation pulse digitized signal
Conjunction method, the approximating method comprises the following steps：
Step S1：The prior model of selected scintillation pulse is biexponential model V (t)=aebt+c·edt, will be described double
Exponential model is defined as object function；
Step S2：The sampled point of classical pulsed in selected scintillation pulse database, the sampled point includes eight voltages
Threshold series and eight time point sequences, wherein, eight voltage threshold sequences are v1, v2, v3, v4, v5, v6, v7 and v8,
Eight time point sequences are t1, t2, t3, t4, t5, t6, t7 and t8；
Step S3：The voltage threshold sequence is saved as into voltage array v=[v1, v2, v3, v4, v5, v6, v7, v8], it is right
The curve of the biexponential model carries out temporal translation, and the translation is concretely comprised the following steps：First time point t1 is put
0, subsequent point in time asks poor with first time point t1 respectively, then by obtained data save as time array t=[0,
(t2-t1), (t3-t1), (t4-t1), (t5-t1), (t6-t1), (t7-t1), (t8-t1)]；
Step S4：Four initial default parameters a, b, c, d of the object function are set to 1, initial parameter number is saved as
Group para=[1,1,1,1]；
Step S5：By the voltage array v, time array t, impulse sampling point number n, the initial parameter array
Para, the object function V (t) are input in the literary Burger-Ma Kuaerte fitting functions of row, are fitted and are obtained four fitting ginsengs
Four fitting parameters are saved as the second parameter array paranew=[a ', b ', c ', d '] by number a ', b ', c ', d '；
Step S6：For each scintillation pulse in scintillation pulse database, except in step S4 with second parameter
Array paranew is replaced outside the initial parameter array para, is repeated in the step S1- step S5, until completing all
The fitting of scintillation pulse, remembers that the function after k-th of scintillation pulse fitting is
Step S7：To the object function V for the scintillation pulse that fitting parameter is determined after fittingk(t) integration obtains k-th of pulse
Energy value Ek；
Step S8：Solve equation Vk(t) curve zero crossing t=0 is obtainedk0, obtain the arrival time t of k-th of pulsek=t1+
tk0, the temporal information of pulse, energy information are extracted and finished.
The prior model of scintillation pulse is collected by digital oscilloscope, and the curve of scintillation pulse includes quick rising
Edge and slow trailing edge.
Scintillation pulse database obtains the digital scintillation pulse of platform record by scintillation pulse and formed.
Scintillation pulse obtains scintillation detector and one of the platform including a pair of opposing and penetrates source, and the source of penetrating is placed in a pair
The centre position of the axial line of the scintillation detector, the scintillation detector accesses the numeral by coaxial cable respectively and shown
Ripple device.
Scintillation detector is Si-BDM detectors, and source is penetrated in the source of penetrating for point-like 18FDG.
Digital oscilloscope is digitized sampling with the sample rate of 16GHz analog bandwidth and 50Gsps, and record is collected
Scintillation pulse.
The prototype of the literary Burger-Ma Kuaerte fitting functions of row for void lmcurve (int n_par, double*par,
Int m_dat, const double*t, const double*y, double (* f) (double t, const double*
Par), const lm_control_struct*control, lm_status_struct*status), wherein, int n_par
The number of parameters of model of fit function is treated in expression；Double*par represents initial parameter value；Int m_dat represent to be fitted sampled point
Number；Const double*t represent the abscissa array of sampled point；Const double*y represent the ordinate of sampled point
Array；Double (* f) (double t, const double*par) represents the curve model of fitting foundation；const lm_
Control_struct*control represents the control parameter of fitting algorithm；Lm_status_struct*status represents fitting
The state parameter of algorithm.
Data type is to include double and float, and for the server that performance is good, configuration is high, data type is set to
Double, otherwise data type be set to float.
Object function Vk(t) limit of integration is 0-200.
Curve zero crossing tk0=[1/ (dk-bk)*ln(-ak/ck)]。
The approximating method of the scintillation pulse digitized signal of the present invention, using row text Burger-Ma Kuaertefa to based on MVT
The digital scintillation pulse signal that method is obtained carries out nonlinear fitting, from biexponential model, by from existing pulse data
The biexponential model parameter extracted in storehouse can greatly improve Riming time of algorithm as the initial value of algorithm, while algorithm is easy in itself
Accelerated in openMP/GPU, can also be gradually stepped up with update algorithm the time performance of computer in itself.Pass through
After this method is met and rebuild to pulse, obtained energy resolution is obviously improved, and this method can not only improve place
Efficiency is managed, and the degree of accuracy and the stability of information extraction are also ensured by this method, therefore, the present invention is in efficiency, standard
Really, the Optimum Fitting Methods under the composite factor such as stable.
Brief description of the drawings
Fig. 1 is the prior model schematic diagram of the pulse of the approximating method of the scintillation pulse digitized signal according to the present invention；
Fig. 2 is the arrangement schematic diagram that scintillation pulse according to an embodiment of the invention obtains platform；
Fig. 3 is the schematic diagram of classical scintillation pulse according to an embodiment of the invention；
Fig. 4 is the fitting side of the scintillation pulse digitized signal of use biexponential model according to an embodiment of the invention
Method is applied to the design sketch that PET signal is handled；
Fig. 5 is the design sketch of energy resolution that is obtained of use straight line exponential model of prior art.
Embodiment
Below in conjunction with specific embodiment, the present invention will be further described.It should be understood that following examples are merely to illustrate this
Invention is not for limitation the scope of the present invention.
The approximating method for the scintillation pulse digitized signal that the present invention is provided, comprises the following steps：
Step S1：The prior model of selected scintillation pulse is biexponential model V (t)=aebt+c·edt, this pair is referred to
Exponential model is defined as object function；
Step S2：The sampled point of classical pulsed in selected scintillation pulse database, the sampled point includes eight voltage thresholds
Value sequence and eight time point sequences, wherein, eight voltage threshold sequences are v1, v2, v3, v4, v5, v6, v7 and v8, at eight
Between point sequence be t1, t2, t3, t4, t5, t6, t7 and t8；
Step S3：Above-mentioned voltage threshold sequence is saved as into voltage array v=[v1, v2, v3, v4, v5, v6, v7, v8], it is right
The curve of biexponential model carries out temporal translation, and the specific method of translation is：First time point t1 is set to 0, when follow-up
Between put and ask poor with t1 respectively, obtained data are saved as into time array t=[0, (t2-t1), (t3-t1), (t4-t1), (t5-
T1), (t6-t1), (t7-t1), (t8-t1)]；
Step S4：Four initial default parameters a, b, c, d of selected target function are 1, save as initial parameter array para
=[1,1,1,1]；
Step S5：By voltage array v, time array t, impulse sampling point number n (n=8), initial parameter array para,
Object function V (t) is input in fitting function lmcurve, is arranged as required to the ginsengs such as corresponding data type, fitting speed
Number, is fitted, and obtained output result is four new fitting parameter a ', b ', c ', d ', by this four new fitting parameters
Save as the second parameter array paranew=[a ', b ', c ', d ']；
Step S6：For the fit procedure of the multiple scintillation pulse data obtained in practical application, except being used in step S4
Second parameter array paranew is replaced outside initial parameter array para, and remaining scintillation pulse processing is repeated in step S1-
Step S5, until completing the fitting of all scintillation pulses, the function after note k-th of scintillation pulse fitting is
Step S7：To the object function V for the scintillation pulse that fitting parameter is determined after fittingk(t) integration obtains k-th of pulse
Energy value Ek；
Step S8：Solve equation Vk(t) curve zero crossing t=0 is obtainedk0(being negative), obtains the arrival time of k-th of pulse
tk=t1+tk0, the temporal information of pulse, energy information are extracted and finished.
In above-mentioned steps S1, the prior model of pulse is collected by digital oscilloscope, as shown in Fig. 2 the priori mould
The scintillation pulse curve of type includes quick rising edge and slow trailing edge, and the shape information of the scintillation pulse can pass through straight line
Index and biexponential model description.Employ biexponential model in the present invention to be described, because the trailing edge of scintillation pulse is non-
Often fast, biexponential model can effectively improve the accuracy of temporal resolution calculating.
In above-mentioned steps S2, scintillation pulse database obtains the digital scintillation pulse of platform record by scintillation pulse and formed.
Fig. 2 is the arrangement schematic diagram that platform 1 is obtained according to the scintillation pulse of one embodiment of the invention, and the scintillation pulse obtains platform 1
Scintillation detector 10 including a pair of opposing and one penetrate source 20, in the embodiment of fig. 2, the flash detection used
Device 10 is Si-BDM detectors, penetrates source 20 and penetrates source for point-like 18FDG, point-like 18FDG penetrates source 20 and is placed in a pair of scintillation detectors
The centre position of 10 axial lines；Two scintillation detectors 10 access digital oscilloscope 30 by coaxial cable 40 respectively, such as,
Coaxial cable 40 is respectively connected to the passage two and passage three of digital oscilloscope；Digital oscilloscope 30 with 16GHz analog bandwidth and
50Gsps sample rate is digitized sampling, the scintillation pulse collected by two passages is recorded, so as to form flicker arteries and veins
Rush database.
According to one embodiment of present invention, the classical pulsed and setting such as Fig. 3 of sampled point used in above-mentioned steps S2
It is shown, wherein, eight voltage threshold sequences are v1, v2, v3, v4, v5, v6, v7 and v8, eight time point sequences be t1, t2,
The setting of the occurrence of voltage threshold can be adjusted according to actual needs in t3, t4, t5, t6, t7 and t8, Fig. 3, herein not
Repeating.
In above-mentioned steps S3, the storage of data can be realized by appropriate operating platform and programming language, such as C++ languages
Speech, will not be repeated here.
In above-mentioned steps S5, the letter of literary Burger-Ma Kuaerte (Levenberg-Marquardt) fitting algorithm of row of selection
Number prototype is void lmcurve (int n_par, double*par, int m_dat, const double*t, const
Double*y, double (* f) (double t, const double*par), const lm_control_struct*
Control, lm_status_struct*status), in the parameter of the function prototype, int n_par represent to treat model of fit letter
Several number of parameters；Double*par represents initial parameter value；Int m_dat represent to be fitted the number of sampled point；const
Double*t represents the abscissa array of sampled point；Const double*y represent the ordinate array of sampled point；double(*
F) (double t, const double*par) represents the curve model of fitting foundation；const lm_control_struct*
Control represents the control parameter of fitting algorithm, such as is fitted the parameter such as speed, fault-tolerant, typically takes default value；lm_status_
Struct*status represents the state parameter of fitting algorithm.
In above-mentioned steps S5, it is arranged as required to the parameters such as corresponding data type, fitting speed and refers to according to required plan
The number size and the memory configurations of system server of the scintillation pulse of conjunction, for the server that performance is good, configuration is high, can set
Data type is put for double, it is float otherwise to set data type；Meanwhile, the control parameter lm_ that the fitting algorithm is carried
Include the parameters such as fitting speed, step, fitting relative error in control_struct*control, these parameters can
Debugged according to current system server, hardware configuration etc., to realize the purpose for improving efficiency and accuracy, for example, for
One embodiment of the present of invention, it is double that data type, which can be set, and the control parameter of remaining fitting algorithm is set to acquiescence
Value.
In above-mentioned steps S7, to Vk(t) the scope 0-200 of integration.
In above-mentioned steps S8, it is order to solve equationSolution obtains curve zero passage
The value t of pointk0=[1/ (dk-bk)*ln(-ak/ck)]。
Fig. 4 is the energy resolution collection of illustrative plates for a scintillation pulse obtain after data processing according to this method, and Fig. 5 is
The design sketch of the energy resolution of the scintillation pulse obtained using straight line exponential model, comparison diagram 4 and Fig. 5 can be seen that this hair
The energy resolution of the bright scintillation pulse for using biexponential model to obtain is 17.9%, compared to the energy using straight line exponential model
Measure resolution ratio 23.4%, it is clear that the energy resolution that the present invention is obtained, which has, to be obviously improved, and this is bright for digital PET system
Aobvious progress.
The present invention obtains scintillation pulse database based on MVT methods, according to default four voltage thresholds, rises in pulse
Edge and trailing edge all obtain four sampled points, i.e., one pulse is represented with eight sampled points (time, contact potential series), by by
The biexponential model parameter extracted in some pulse databases as fitting algorithm initial value, can greatly improve algorithm operation when
Between, this method is also easy to openMP/GPU and accelerated in itself, and this method has accomplished the balance of stability and accuracy, complete
Efficiency and algorithm stability are improved in the case of the scintillation pulse for reducing biexponential model, the PET finally obtained according to the method
System capacity resolution ratio is significantly increased.
Above-described, only presently preferred embodiments of the present invention is not limited to the scope of the present invention, of the invention is upper
Stating embodiment can also make a variety of changes.What i.e. every claims and description according to the present patent application were made
Simply, equivalent changes and modifications, falls within the claims of patent of the present invention.The present invention not detailed description is
Routine techniques content.
Claims (10)
1. a kind of approximating method of scintillation pulse digitized signal, it is characterised in that the approximating method comprises the following steps：
Step S1：The prior model of selected scintillation pulse is biexponential model V (t)=aebt+c·edt, by described pair of index mould
Type is defined as object function；
Step S2：The sampled point of classical pulsed in selected scintillation pulse database, the bar point of adopting includes eight voltage thresholds
Sequence and eight time point sequences, wherein, eight voltage threshold sequences are v1, v2, v3, v4, v5, v6, v7 and v8, eight
The time point sequence is t1, t2, t3, t4, t5, t6, t7 and t8；
Step S3：The voltage threshold sequence is saved as into voltage array v=[v1, v2, v3, v4, v5, v6, v7, v8], to described
The curve of biexponential model carries out temporal translation, and the translation is concretely comprised the following steps：First time point t1 is set to 0, after
Continuous time point asks poor with first time point t1 respectively, and obtained data then are saved as into time array t=[0, (t2-
T1), (t3-t1), (t4-t1), (t5-t1), (t6-t1), (t7-t1), (t8-t1)]；
Step S4：Four initial default parameters a, b, c, d of the object function are set to 1, initial parameter array is saved as
Para=[1,1,1,1]；
Step S5：Bar point number n, the initial parameter array are adopted into the voltage array v, the time array t, the pulse
Para, the object function V (t) are input in the literary Burger-Ma Kuaerte fitting functions of row, are fitted and are obtained four fitting ginsengs
Four fitting parameters are saved as the second parameter array paranew=[a ', b ', c ', d '] by number a ', b ', c ', d '；
Step S6：For each scintillation pulse in the scintillation pulse database, except in step S4 with second parameter
Array paranew is replaced outside the initial parameter array para, is repeated in step S5 described in the step S1-, until completing
The fitting of all scintillation pulses, remembers that the function after k-th of scintillation pulse fitting is
Step S7：To the object function V for the scintillation pulse that fitting parameter is determined after fittingk(t) integration obtains the energy of k-th of pulse
Value Ek；
Step S8：Solve equation Vk(t) curve zero crossing t=0 is obtainedk0, obtain the arrival time t of k-th of pulsek=t1+tk0, arteries and veins
The temporal information of punching, energy information are extracted and finished.
2. the approximating method of scintillation pulse digitized signal according to claim 1, it is characterised in that the scintillation pulse
Prior model collected by digital oscilloscope, under the curve of the scintillation pulse includes quick rising edge and is slow
Edge drops.
3. the approximating method of scintillation pulse digitized signal according to claim 2, it is characterised in that the scintillation pulse
Database obtains the digital scintillation pulse of platform record by scintillation pulse and formed.
4. the approximating method of scintillation pulse digitized signal according to claim 3, it is characterised in that the scintillation pulse
Obtain scintillation detector and one of the platform including a pair of opposing and penetrate source, the source of penetrating is placed in flash detection described in a pair
The centre position of device axial direction line, the scintillation detector accesses the digital oscilloscope by coaxial cable respectively.
5. the approximating method of scintillation pulse digitized signal according to claim 4, it is characterised in that the flash detection
Device is Si-BDM detectors, and source is penetrated in the source of penetrating for point-like 18FDG.
6. the approximating method of scintillation pulse digitized signal according to claim 5, it is characterised in that the digital oscillography
Device is digitized sampling with the sample rate of 16GHz analog bandwidth and 50Gsps, records the scintillation pulse collected.
7. the approximating method of scintillation pulse digitized signal according to claim 1, it is characterised in that the Lie Wenbai
The prototype of Ge-Ma Kuaerte fitting functions is void lmcurve (int n_par, double*par, int m_dat, const
Double*t, const double*y, double (* f) (double t, const double*par), const lm_
Control_struct*control, lm_status_struct*status), wherein, int n_par represent to treat model of fit
The number of parameters of function；Double*par represents initial parameter value；Int m_dat represent to be fitted the number for adopting bar point；const
Double*t represents to adopt the abscissa array of bar point；Const double*y represent the ordinate array of sampled point；double(*
F) (double t, const double*par) represents the curve model of fitting foundation；const lm_control_struct*
Control represents the control parameter of fitting algorithm；Lm_status_struct*status represents the state parameter of fitting algorithm.
8. the approximating method of scintillation pulse digitized signal according to claim 1, it is characterised in that the data type
It is to include double and float, for the server that performance is good, configuration is high, data type is set to double, otherwise data class
Type is set to float.
9. the approximating method of scintillation pulse digitized signal according to claim 1, it is characterised in that the object function
Vk(t) limit of integration is 0-200.
10. the approximating method of scintillation pulse digitized signal according to claim 1, it is characterised in that the curve mistake
Zero point tk0=[1/ (dk-bk)*ln(-ak/ck)]。
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|---|---|---|---|
| CN201710247652.9A CN107024711B (en) | 2017-04-17 | 2017-04-17 | A kind of approximating method of scintillation pulse digitized signal |
| EP17906084.3A EP3614181A4 (en) | 2017-04-17 | 2017-08-28 | Method for fitting flickering pulse digitized signals |
| PCT/CN2017/099238 WO2018192151A1 (en) | 2017-04-17 | 2017-08-28 | Method for fitting flickering pulse digitized signals |
| JP2019555760A JP6875548B2 (en) | 2017-04-17 | 2017-08-28 | Scintillation pulse digital signal fitting method |
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| CN201710247652.9A CN107024711B (en) | 2017-04-17 | 2017-04-17 | A kind of approximating method of scintillation pulse digitized signal |
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| WO2018192151A1 (en) * | 2017-04-17 | 2018-10-25 | 苏州瑞派宁科技有限公司 | Method for fitting flickering pulse digitized signals |
| CN109171787A (en) * | 2018-08-27 | 2019-01-11 | 苏州瑞派宁科技有限公司 | The method of sampling, device and the computer program medium of pulse signal |
| CN109350098A (en) * | 2018-08-27 | 2019-02-19 | 苏州瑞派宁科技有限公司 | Determination method, method for reconstructing and the device of the fit approach of signal |
| CN109444559A (en) * | 2018-10-26 | 2019-03-08 | 苏州瑞迈斯医疗科技有限公司 | The method of sampling, method for reconstructing and the device of pulse signal |
| CN109669206A (en) * | 2019-03-03 | 2019-04-23 | 南昌华亮光电有限责任公司 | Circulating type liquid scintillator intelligence energy disperse spectroscopy system and its signal processing method |
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| EP3614181A1 (en) | 2020-02-26 |
| EP3614181A4 (en) | 2020-12-16 |
| JP6875548B2 (en) | 2021-05-26 |
| CN107024711B (en) | 2019-02-26 |
| WO2018192151A1 (en) | 2018-10-25 |
| JP2020516889A (en) | 2020-06-11 |
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